LinkedIn Clone

This project’s structure and ideas are the same as he real linkedIn webiste

This documentation is designed to be consumed by both humans and AI agents. It provides comprehensive information about the backend services, APIs, data models, and integration patterns.

Detailed Documentation Files

For comprehensive documentation, the following detailed files are available:

Documentation Overview

LinkedIn Clone

Version : 1.0.2

This project's structure and ideas are the same as he real linkedIn webiste

How to Use Project Documents

The Linkedin project has been designed and generated using Mindbricks, a powerful microservice-based backend generation platform. All documentation is automatically produced by the Mindbricks Genesis Engine, based on the high-level architectural patterns defined by the user or inferred by AI.

This documentation set is intended for both AI agents and human developers—including frontend and backend engineers—who need precise and structured information about how to interact with the backend services of this project. Each document reflects the live architecture of the system, providing a reliable reference for API consumption, data models, authentication flows, and business logic.

By following this documentation, developers can seamlessly integrate with the backend, while AI agents can use it to reason about the service structure, make accurate decisions, or even generate compatible client-side code.

Accessing Project Services

Each service generated by Mindbricks is exposed via a dedicated REST API endpoint. Every service documentation set includes the base URL of that service along with the specific API paths for each available route.

Before consuming any API, developers or agents must understand the service URL structure and environment-specific endpoints.

Service Endpoint Structure

Environment URL Pattern Example
Preview https://linkedin.prw.mindbricks.com/auth-api
Staging https://linkedin-stage.mindbricks.co/auth-api
Production https://linkedin.mindbricks.co/auth-api

Replace auth with the actual service name as lower case (e.g., order-api, bff-service, customermanagement-api etc.).

Environment Usage Notes

Frontend applications should be designed to easily switch between environments, allowing dynamic endpoint targeting for Preview, Staging, and Production.

Getting Started: Use the Auth Service First

Before interacting with other services in the Linkedin project, AI agents and developers should begin by integrating with the Auth Service.

Mindbricks automatically generates a dedicated authentication microservice based on the project’s authentication definitions provided by the architect. This service provides the essential user and access management foundation for the project.

Agents should first utilize the Auth Service to:

Auth Service Documentation

Use the following resources to understand and integrate the Auth Service:

Note: For most frontend use cases, the REST API Guide will be the primary source. The Event Guide and Service Design documents are especially useful when integrating with other backend microservices or building systems that interact with the auth service indirectly.

Using the BFF (Backend-for-Frontend) Service

In Mindbricks, all backend services are designed with an advanced CQRS (Command Query Responsibility Segregation) architecture. Within this architecture, business services are responsible for managing their respective domains and ensuring the accuracy and freshness of domain data.

The BFF service complements these business services by providing a read-only aggregation and query layer tailored specifically for frontend and client-side applications.

Key Principles of the BFF Service

BFF Service Documentation

Tip: Use the BFF service as the main entry point for all frontend data queries. It simplifies access, reduces round-trips, and ensures that data is shaped appropriately for the UI layer.

Business Services Overview

The LinkedIn Clone project consists of multiple business services, each responsible for managing a specific domain within the system. These services expose their own REST APIs and documentation sets, and are accessible based on the environment (Preview, Staging, Production).

Usage Guidance

Business services are primarily designed to:

For advanced query needs across multiple services or aggregated views, prefer using the BFF service.

Available Business Services

jobApplication Service

Description: Microservice handling job postings (created by recruiters/company admins), job applications (created by users), allowing job search, application submission, and status update workflows. Enforces business rules around application status, admin controls, and lets professionals apply and track job applications .within the network.

Documentation:

Base URL Examples:

Environment URL
Preview https://linkedin.prw.mindbricks.com/jobapplication-api
Staging https://linkedin-stage.mindbricks.co/jobapplication-api
Production https://linkedin.mindbricks.co/jobapplication-api

networking Service

Description: Handles professional networking logic for user-to-user connections: manages connection requests, accepted relationships, listing/removal, permissions, and state transitions. Publishes connection lifecycle events for notification…

Documentation:

Base URL Examples:

Environment URL
Preview https://linkedin.prw.mindbricks.com/networking-api
Staging https://linkedin-stage.mindbricks.co/networking-api
Production https://linkedin.mindbricks.co/networking-api

company Service

Description: Handles company profiles, company admin assignments, company following, and posting company updates/news. Enables professionals to follow companies, get updates, and enables admins to manage company presence…

Documentation:

Base URL Examples:

Environment URL
Preview https://linkedin.prw.mindbricks.com/company-api
Staging https://linkedin-stage.mindbricks.co/company-api
Production https://linkedin.mindbricks.co/company-api

content Service

Description: Handles creation, editing, and deletion of user posts (with attachments and visibility), user post feed aggregation, and post engagement (likes, comments). All with post-level visibility control (public/private)…

Documentation:

Base URL Examples:

Environment URL
Preview https://linkedin.prw.mindbricks.com/content-api
Staging https://linkedin-stage.mindbricks.co/content-api
Production https://linkedin.mindbricks.co/content-api

messaging Service

Description: Handles direct, private 1:1 and group messaging between users, conversation management, and message history/storage…

Documentation:

Base URL Examples:

Environment URL
Preview https://linkedin.prw.mindbricks.com/messaging-api
Staging https://linkedin-stage.mindbricks.co/messaging-api
Production https://linkedin.mindbricks.co/messaging-api

profile Service

Description: Handles user professional profiles, including experience, education, skills, languages, certifications, profile photo, and visibility controls. Enables recruiter search, elastic-style indexing, and profile editing, with all data linked to authenticated users…

Documentation:

Base URL Examples:

Environment URL
Preview https://linkedin.prw.mindbricks.com/profile-api
Staging https://linkedin-stage.mindbricks.co/profile-api
Production https://linkedin.mindbricks.co/profile-api

agentHub Service

Description: AI Agent Hub

Documentation:

Base URL Examples:

Environment URL
Preview https://linkedin.prw.mindbricks.com/agenthub-api
Staging https://linkedin-stage.mindbricks.co/agenthub-api
Production https://linkedin.mindbricks.co/agenthub-api

Connect via MCP (Model Context Protocol)

All backend services in the Linkedin project expose their Business APIs as MCP tools. These tools are aggregated by the MCP-BFF service into a single unified endpoint that external AI tools can connect to.

Unified MCP Endpoint

Environment StreamableHTTP (recommended) SSE (legacy fallback)
Preview https://linkedin.prw.mindbricks.com/mcpbff-api/mcp https://linkedin.prw.mindbricks.com/mcpbff-api/mcp/sse
Staging https://linkedin-stage.mindbricks.co/mcpbff-api/mcp https://linkedin-stage.mindbricks.co/mcpbff-api/mcp/sse
Production https://linkedin.mindbricks.co/mcpbff-api/mcp https://linkedin.mindbricks.co/mcpbff-api/mcp/sse

Authentication

MCP connections require authentication via the Authorization header:

OAuth is not supported for MCP connections at this time.

Connecting from Cursor

Add the following to your project’s .cursor/mcp.json:

{
  "mcpServers": {
    "linkedin": {
      "url": "https://linkedin.prw.mindbricks.com/mcpbff-api/mcp",
      "headers": {
        "Authorization": "Bearer sk_mbx_your_api_key_here"
      }
    }
  }
}

Connecting from Claude Desktop

Add to your Claude Desktop configuration (claude_desktop_config.json):

{
  "mcpServers": {
    "linkedin": {
      "url": "https://linkedin.prw.mindbricks.com/mcpbff-api/mcp",
      "headers": {
        "Authorization": "Bearer sk_mbx_your_api_key_here"
      }
    }
  }
}

What’s Available

Once connected, the AI tool can discover and call all Business API tools from all services — CRUD operations, custom queries, file operations, and more. The MCP-BFF handles routing each tool call to the correct backend service and propagates your authentication context.

Conclusion

This documentation set provides a comprehensive guide for understanding and consuming the LinkedIn Clone backend, generated by the Mindbricks platform. It is structured to support both AI agents and human developers in navigating authentication, data access, service responsibilities, and system architecture.

To summarize:

Each service offers a complete set of documentation—REST API guides, event interface definitions, and design insights—to help you integrate efficiently and confidently.

Whether you are building a frontend application, configuring an automation agent, or simply exploring the architecture, this documentation is your primary reference for working with the backend of this project.

For environment-specific access, ensure you’re using the correct base URLs (Preview, Staging, Production), and coordinate with the project owner for any custom deployments.

Table of Contents

Getting Started

Frontend Prompts

Auth Service

Data Objects

Business APIs

Database Buckets

JobApplication Service

Data Objects

Business APIs

Networking Service

Data Objects

Business APIs

Company Service

Data Objects

Business APIs

Content Service

Data Objects

Business APIs

Messaging Service

Data Objects

Business APIs

Profile Service

Data Objects

Business APIs

AgentHub Service

Data Objects

Business APIs

Bff Service

Notification Service

LLM Documents

API Endpoints Summary

linkedin-auth-service Service

linkedin-jobapplication-service Service

linkedin-networking-service Service

linkedin-company-service Service

linkedin-content-service Service

linkedin-messaging-service Service

linkedin-profile-service Service

linkedin-agenthub-service Service

Getting Started

  1. Authentication: Start with the Auth Service to register and authenticate users
  2. Data Queries: Use the BFF Service for optimized read-only data queries
  3. Business Operations: Use individual business services for create/update/delete operations

Additional Resources

Generated by Mindbricks Genesis Engine